Analytics Engineer 5 - Ads

Netflix•New York, NY

1d•$330,000 - $566,000

About The Position

The Ads Data & Insights team's mission at Netflix is to help build the foundation of the Ads business. We design effective metrics, conduct analyses and develop analytic tools, and build predictive models and algorithms using machine learning - all with the goal of creating more choices and joy for our members. We are seeking a Senior Analytics Engineer to lead the development of a unified revenue analytics narrative and strategy for Netflix’s global Ads business. Building upon our growing data infrastructure, we need an end-to-end owner to operationalize core revenue datasets and drive the overarching business narrative. In this highly impactful role, you will build the semantic models, executive dashboards, and analysis frameworks that drive how we measure, reconcile, and communicate revenue across diverse stakeholder groups. As a subject matter expert, you will play a pivotal role in shaping the analytics vision for revenue measurement. You will take foundational revenue definitions and champion them across Finance & Strategy, Revenue Accounting, and Product. This is an open opportunity to explore how we measure and think about revenue across the entire Ads business—empowering Netflix to deliver accurate, transparent, and timely insights that cascade into key downstream performance metrics.

Requirements

Experience working with financial datasets, revenue accounting, or ad-tech monetization analytics.
A “Data Product Owner” mindset. You are comfortable with ambiguity and recognize that defining the metric across a matrixed organization is just as important as writing the code to build it.
Communication superpower — the ability to communicate, influence, and connect the dots between insights and actions across a variety of stakeholders.
Fluency in SQL, workflow orchestration tools like Apache Airflow, and at least one analytics and scripting language like Python.
Mentors, brainstorms with, and enables others, especially within your functional area.
A proven track record of balancing the need to move quickly with the high rigor and accuracy required for executive and financial reporting.
Strong analytical rigor combined with the ability to conduct independent research and explain complex metric variances to senior leadership.

Nice To Haves

Experience building or working with semantic modeling tools like LookML for creating and managing metric contracts is a plus.
Curiosity or practical experience building with emerging AI technologies (e.g., Agentic AI) is a plus.

Responsibilities

Lead the analytics vision for unified revenue measurement across Netflix Ads, designing and implementing frameworks to harmonize, quantify, and report on diverse revenue streams, including new content formats Netflix is launching, like Live and Free-to-air Broadcasting.
Act as the lead Semantic Architect for revenue, driving consensus across F&S, Accounting, and Product, and codifying those agreed-upon definitions into the Ads Metrics Catalog (AMC) and our underlying semantic models.
Build scalable, transparent data models and dashboards—in partnership with Data Engineering—that provide real-time and periodic insights into revenue streams, metric definitions, and the impact of adjustments, supporting daily operational needs and strict financial and SOX compliance reporting.
Drive the narrative around how core revenue definitions impact downstream performance metrics (like CPM and CPS), conducting deep-dive research to explain the why behind metric movements.
Act as a subject matter expert in revenue analytics, piloting scalable solutions for complex treatments (e.g., invoice discounts, agency fees, FX rates, makegoods, and integrated marketing fees), and driving innovation and transparency in how Netflix measures and communicates advertising revenue.
Serve as the integration layer for revenue data. While partner teams may own localized source data (Sales, Live, etc.), you will be responsible for aggregating, harmonizing, and exposing the overarching executive revenue views in core reporting surfaces.